Hepatocellular carcinoma (HCC) is considered to be a terminally-ill disease and currently, there is little progress toward the discovery of efficient therapies leading to regression. This is due largely to the lack of a method for early diagnosis and the lack of information on the phenotypic changes associated with the development of HCC. Changes in gene expression during the genesis of HCC are largely unknown (http://www.ncbi.nlm.nih.gov/ncicgap/). Our goals are to identify genes expressed during the development of HCC and to discover new genes critical for viral hepatitis-mediated HCC. These studies will contribute to the establishment of novel markers with potential diagnostic and prognostic value, and analysis of these genes would provide further understanding of the genesis of liver cancer and provide further insights into designing strategies for HCC-directed molecular therapy. We have taken two approaches, namely, Serial Analysis of Gene Expression (SAGE) and cDNA microarray, to explore potential cellular genes that are expressed abnormally in primary human hepatocytes infected with the two viral hepatitis oncoproteins, HBx or HC-core, and in liver samples from chronic active hepatitis patients or HCC patients that differ in the status of HBV or HCV. In addition, we are comparing gene expression profiles between primary HCC and metastatic HCC. Infection of normal hepatocytes with HBx and HC-core is achieved by a replication-defective adenoviral vector. Using SAGE, we have constructed a library derived from primary human hepatocytes infected with HBx. Among over 10,000 transcripts (more than 750 unique genes) analyzed, 32 genes were upregulated at least 3-fold and 40 genes were downregulated in at least 3-fold by HBx. Sequence search indicates that some of these transcripts are known genes while several others are either unknown or can only be found in the EST database. We also are utilizing the NCI human microarray that contains either 2208 or 6500 human cDNAs to analyze RNA samples of human primary hepatocytes infected with HBx vs. control, HBV and HCV infected liver tissues vs. normal tissues, and tumor vs. non-tumorous tissues from HCC patients. Clustering algorithms were used to identify deregulation of distinctive gene expression profiles in these samples. Northern blotting analysis was used to verify the microarray data. We have identified multiple genes that are either up- or down-regulated in these samples. Further analysis of these genes will be useful for understanding the mechanism of HBV- and HCV-mediated oncogenesis.